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Abstract:

In a motion tracking method using an image capturing device that is
installed on a track system, images of a monitored area are captured in
real-time using a lens of the image capturing device. The captured images
are analyzed to check for motion in the monitored area, and a movement
direction of the motion is determined when the motion is detected in the
monitored area. The image capturing device is controlled to move along
the track system to track the motion using a driving device according to
the movement direction.

Claims:

1. A motion tracking method using an image capturing device, the image
capturing device being installed on a track system, the method
comprising: capturing images of a monitored area using a lens of the
image capturing device in real-time; analyzing the captured images to
check for motion in the monitored area; determining a movement direction
of the motion when the motion is detected in the monitored area; and
controlling the image capturing device to move along the track system to
track the motion using a driving device according to the movement
direction.

2. The method according to claim 1, wherein the motion is defined as
movements of people in the monitored area.

3. The method according to claim 2, wherein the captured images are
analyzed by using a template matching method that uses a neural network
training algorithm or an adaptive boosting (AdaBoost) algorithm.

4. The method according to claim 1, wherein the movement direction of the
motion is determined by comparing positions of the motion within two
images of the monitored area that are consecutively captured by the lens.

5. The method according to claim 1, further comprising: extracting a
smallest rectangle enclosing the motion from a current image of the
monitored area; determining whether a ratio of the smallest rectangle
within the current image is less than a preset value after the image
capturing device has been controlled to move; controlling the image
capturing device to pan and/or tilt the lens until a center of the
smallest rectangle is coincident with a center of the current image of
the monitored area if the ratio of the smallest rectangle within the
current image is less than the preset value; and controlling the image
capturing device to zoom in the lens to obtain a zoomed image of the
motion until the ratio of the smallest rectangle within the current image
is equal to or greater than the preset value.

6. The method according to claim 1, wherein the image capturing device is
a speed dome camera or a pan/tilt/zoom (PTZ) camera.

7. An image capturing device for motion tracking, the image capturing
device being installed on a track system, the image capturing device
comprising: a lens, a driving device, at least one processor, and a
storage system; and one or more programs stored in the storage system and
being executable by the at least one processor, wherein the one or more
programs comprises: a capturing module operable to capture images of a
monitored area using the lens in real-time; a detection module operable
to analyze the captured images to check for motion in the monitored area;
a determination module operable to determine a movement direction of the
motion when the motion is detected in the monitored area; and an
execution module operable to control the image capturing device to move
along the track system to track the motion using the driving device
according to the movement direction.

8. The image capturing device according to claim 7, wherein the motion is
defined as movements of people in the monitored area.

9. The image capturing device according to claim 8, wherein the captured
images are analyzed by using a template matching method that uses a
neural network training algorithm or an adaptive boosting (AdaBoost)
algorithm.

10. The image capturing device according to claim 7, wherein the movement
direction of the motion is determined by comparing positions of the
motion within two images of the monitored area that are consecutively
captured by the lens.

11. The image capturing device according to claim 7, wherein the
detection module is further operable to extract a smallest rectangle
enclosing the motion from a current image of the monitored area, and
determine whether a ratio of the smallest rectangle within the current
image is less than a preset value after the image capturing device has
been controlled to move.

12. The image capturing device according to claim 11, wherein the
execution module is further operable to control the image capturing
device to pan and/or tilt the lens until a center of the smallest
rectangle is coincident with a center of the current image of the
monitored area if the ratio of the smallest rectangle within the current
image is less than the preset value, and control the image capturing
device to zoom in the lens to obtain a zoomed image of the motion until
the ratio of the smallest rectangle within the current image is equal to
or greater than the preset value.

13. The image capturing device according to claim 7, wherein the image
capturing device is a speed dome camera or a pan/tilt/zoom (PTZ) camera.

14. A non-transitory storage medium storing a set of instructions, the
set of instructions capable of being executed by a processor of an image
capturing device that is installed on a track system, causing the image
capturing device to perform a motion tracking method, the method
comprising: capturing images of a monitored area using a lens of the
image capturing device in real-time; analyzing the captured images to
check for motion in the monitored area; determining a movement direction
of the motion when the motion is detected in the monitored area; and
controlling the image capturing device to move along the track system to
track the motion using a driving device of the image capturing device
according to the movement direction.

15. The storage medium as claimed in claim 14, wherein the motion is
defined as movements of people in the monitored area.

16. The storage medium as claimed in claim 15, wherein the captured
images are analyzed by using a template matching method that uses a
neural network training algorithm or an adaptive boosting (AdaBoost)
algorithm.

17. The storage medium as claimed in claim 14, wherein the movement
direction of the motion is determined by comparing positions of the
motion within two images of the monitored area that are consecutively
captured by the lens.

18. The storage medium as claimed in claim 14, wherein the method further
comprises: extracting a smallest rectangle enclosing the motion from a
current image of the monitored area; determining whether a ratio of the
smallest rectangle within the current image is less than a preset value
after the image capturing device has been controlled to move; controlling
the image capturing device to pan and/or tilt the lens until a center of
the smallest rectangle is coincident with a center of the current image
of the monitored area if the ratio of the smallest rectangle within the
current image is less than the preset value; and controlling the image
capturing device to zoom in the lens to obtain a zoomed image of the
motion until the ratio of the smallest rectangle within the current image
is equal to or greater than the preset value.

19. The storage medium as claimed in claim 14, wherein the image
capturing device is a speed dome camera or a pan/tilt/zoom (PTZ) camera.

Description:

BACKGROUND

[0001] 1. Technical Field

[0002] Embodiments of the present disclosure relate generally to
surveillance technology, and more particularly, to an image capturing
device and a motion tracking method using the image capturing device.

[0003] 2. Description of Related Art

[0004] Cameras installed on a track system have been used to perform
security surveillance by capturing images of a monitored area. A typical
camera installed on the track system can automatically and can regularly
move along the track system but cannot move according to specific
movements.

BRIEF DESCRIPTION OF THE DRAWINGS

[0005] FIG. 1 is a block diagram of one embodiment of an image capturing
device.

[0006] FIG. 2 is a schematic diagram illustrating one example of the image
capturing device installed on a track system.

[0007] FIGS. 3A-3C are schematic diagrams of one embodiment of controlling
movements of the image capturing device along the track system according
to a specific motion.

[0008] FIGS. 4A-4B are schematic diagrams of one embodiment of zooming in
a lens of the image capturing device.

[0009] FIG. 5 is a flowchart of one embodiment of a motion tracking method
using the image capturing device of FIG. 1.

DETAILED DESCRIPTION

[0010] The disclosure, including the accompanying drawings, is illustrated
by way of example and not by way of limitation. It should be noted that
references to "an" or "one" embodiment in this disclosure are not
necessarily to the same embodiment, and such references mean at least
one.

[0011] FIG. 1 is a block diagram of one embodiment of an image capturing
device 1. In the embodiment, the image capturing device 1 includes a lens
10, a driving device 11, a processor 12, and a storage system 13. The
image capturing device 1 may further include a capturing module 101, a
detection module 102, a determination module 103, and an execution module
104. It should be apparent that FIG. 1 is only one example of the image
capturing device 1 that can be included with more or fewer components
than shown in other embodiments, or a different configuration of the
various components.

[0012] Each of the modules 101-104 may include one or more computerized
instructions in the form of one or more programs that are stored in the
storage system 13 or a computer-readable medium, and executed by the
processor 12 to perform operations of the image capturing device 1. In
general, the word "module", as used herein, refers to logic embodied in
hardware or firmware, or to a collection of software instructions,
written in a programming language, such as, Java, C, or Assembly. One or
more software instructions in the modules may be embedded in firmware,
such as EPROM. The modules described herein may be implemented as either
software and/or hardware modules and may be stored in any type of
computer-readable medium or other storage device.

[0013] Referring to FIG. 2, the image capturing device 1 is installed on a
track system 3. The track system 3 comprises one or more tracks, and the
image capturing device 1 can be controlled to move along the tracks
according to a specific motion that is detected in a monitored area, such
as movements of people. In one embodiment, the image capturing device 1
may be a speed dome camera or a pan/tilt/zoom (PTZ) camera, for example.
The track system 3 may be installed on the top of the monitored area or
other suitable locations.

[0014] The lens 10 may include a charge coupled device (CCD) for capturing
images of the monitored area. The monitored area may be the interior of a
warehouse, a supermarket, a bank, or other place to be monitored. The
driving device 11 may be used to drive the image capturing device 1 to
move along the tracks of the track system 3. In one embodiment, the
driving device 11 may be composed of one or more servo motors.

[0015] The capturing module 101 is operable to capture images of the
monitored area using the lens 10 in real-time. In the embodiment, the
capturing module 101 may capture an image of the monitored area at
regular intervals, such as, one second, or two seconds.

[0016] The detection module 102 is operable to analyze the captured images
to check for motion in the monitored area. In the embodiment, the motion
may be defined as movements of people in the monitored area. The captured
images are two dimension (2D) images. The detection module 102 may use a
2D image analysis method to analyze the images. In one embodiment, the 2D
image analysis method may be a template matching method using a neural
network training algorithm or an adaptive boosting (AdaBoost) algorithm.
A detailed description is provided as follows.

[0017] The detection module 102 may compare each of the captured images
with a plurality of 2D templates of people to check for a region that is
the same as or similar to any one of the templates. In the embodiment,
the 2D templates of people may be pre-collected and stored in the storage
system 13. When a region that is checked is the same or similar to any
one of the templates, a person is detected in the monitored area. Then
the detection module 102 extracts the region from one of the captured
images of the monitored area in which the person is detected.

[0018] The determination module 103 is operable to determine a movement
direction of the motion when the motion is detected in the monitored
area. In the embodiment, the determination module 103 may determine the
movement direction of the motion by comparing positions of the motion
within two images of the monitored area consecutively captured by the
lens 10.

[0019] The execution module 104 is operable to control the image capturing
device 1 to move along the track system 3 to track the motion according
to the movement direction using the driving device 11. For example, if a
person moves towards the left of the monitored area, the execution module
104 may control the image capturing device 1 to move towards the left of
the track system 3. If the person moves towards the right of the
monitored area, the execution module 104 may control the image capturing
device 1 to move towards the right of the track system 3.

[0020] Referring to FIGS. 4A-4C, the image capturing device 1 moves from a
first position "A1" to a second position "A2" along the track system 3
when a person 4 moves towards the right of the monitored area. Then, the
image capturing device 1 further moves from the second position "A2" to a
third position "A3" along the track system 3 when the person 4 further
moves towards the right.

[0021] FIG. 5 is a flowchart of one embodiment of a motion tracking method
using the image capturing device 1 of FIG. 1. Depending on the
embodiment, additional blocks may be added, others removed, and the
ordering of the blocks, may be changed.

[0022] In block S01, the capturing module 101 captures images of the
monitored area using the lens 10 in real-time. In the embodiment, the
capturing module 101 may capture an image of the monitored area at
regular intervals, such as, one second, or two seconds.

[0023] In block S02, the detection module 102 analyzes the captured images
to check for motion in the monitored area. In block S03, the detection
module 102 determines whether motion is detected in the monitored area.
If motion is detected in the monitored area, block S04 is implemented.
Otherwise, if no motion is detected in the monitored area, block S02 is
repeated.

[0024] In block S04, the determination module 103 determines a movement
direction of the motion. In the embodiment, the determination module 103
may determine the movement direction of the motion by comparing positions
of the motion within two images of the monitored area that are
consecutively captured by the lens 10.

[0025] In block S05, the extraction module 104 controls the image
capturing device 1 to move along the track system 3 to track the motion
using the driving device 11 according to the movement direction of the
motion. Details of controlling the movement of the image capturing device
1 have been provided above.

[0026] In other embodiments, the detection module 102 further extracts a
smallest rectangle enclosing the motion from a current image of the
monitored area, and determines whether a ratio of the smallest rectangle
within the current image is less than a preset value (e.g., 20%) after
the image capturing device 1 has been controlled to move. If the ratio of
the smallest rectangle within the current image is less than the preset
value, the execution module 104 further controls the image capturing
device 1 to pan and/or tilt the lens 10 until a center of the smallest
rectangle is coincident with a center of the current image of the
monitored area. In order to obtain a zoomed image of the motion, the
execution module 104 further controls the image capturing device 1 to
zoom in the lens 10 until the ratio of the smallest rectangle within the
current image is equal to or greater than the preset value. As an
example, referring to FIGS. 4A-4B, "D1" represents an image of the
monitored area captured by the lens 10 when a person 4 is detected from
the monitored area. "D2" represents another image of the monitored area
captured by the lens 10 when the lens 10 is zoomed in.

[0027] Although certain embodiments of the present disclosure have been
specifically described, the present disclosure is not to be construed as
being limited thereto. Various changes or modifications may be made to
the present disclosure without departing from the scope and spirit of the
present disclosure.